Harvard Catalyst Profiles

Our goals are to identify novel genetic associations with sleep apnea and insomnia (the two most common sleep disorders) and to stratify patients into different disease subtypes based on patterns found in electronic health records (EHRs). This is a computational project that will leverage natural language processing, R, Python, whole-genome sequencing (WGS) and other omics analyses, and Linux-based computer cluster programming. I am the PI of an R01 project that will combine data from three major clinical biobanks with hundreds of thousands of patients. I am also the co-chair of the NHLBI TOPMed Consortium's Sleep Traits Working Group, where there are additional WGS datasets available. We anticipate multiple publication opportunities, which you could help lead. Additional opportunities are also possible, including the analysis of other sleep disorders and the relationship between sleep apnea, COVID-19 severity, and long COVID.

We are a computational group specializing in a) the genetic epidemiology of sleep disorders and b) the relationship between sleep disorders and comorbidities, including COVID-19 and PASC (post-acute sequelae of SARS-CoV-2 infection). We are funded by the NHLBI and the American Thoracic Society Foundation to address these questions: Genetic Epidemiology of Sleep Apnea and Comorbidities in Biobanks: In this NHLBI R01 project, we are investigating the genetics of sleep apnea and insomnia at scale by leveraging electronic health record biobanks from three institutions and whole-genome sequencing from the TOPMed Consortium (where I co-chair the Sleep Traits working group). We are also investigating the relationship between sleep disorders and comorbidities using natural language processing and other methods, with data from over 250,000 participants currently extracted. Pulmonary Disease Contributions to COVID-19 Morbidity and Mortality: In this American Thoracic Society Foundation project, we are expanding on our prior work discovering a relationship between sleep apnea and COVID-19 severity to now include other pulmonary disorders and more advanced methods. We have assembled data from over 30,000 patients with COVID-19. An overview of current highlights from Fall 2021 can be found from our NHLBI workshop presentation (https://www.nhlbi.nih.gov/events/2021/identifying-research-directions-sleep-circadian-biology-and-covid-19 ).